National trial: Computer predicts patient outcomes based on EEG.

Magnetic memory device is smallest demonstrated and uses record-low current.

AI can merge overlapping and incomplete medical datasets and then determine which variables are causative, giving new possibilities for old data; scientists at Babylon demonstrated the potential of the AI on data from tumors and protein structures.

Conventional computing hardware are inefficient to tackle data-intensive artificial-intelligence tasks due to the underlying von Neumann architecture restriction.

A novel method of combining advanced optical imaging with an artificial intelligence algorithm produces accurate, real-time intraoperative diagnosis of brain tumors, a new study finds.

The increased freshwater from melting Antarctic ice sheets plus increased wind has reduced the amount of oxygen in the Southern Ocean and made it more acidic and warmer.

This technology could contribute to personalized medicine by making highly accurate prediction of cancer recurrence possible by acquiring new knowledge from images.

FIMM researchers have developed an efficient machine learning model that requires only a limited set of dose-response measurements for accurate prediction of drug combination synergy in a given patient sample. The minimal-input web-implementation, named DECREASE, supports cost-effective combinatorial screening in precision medicine projects with decreased experimental costs, translational time and number of patient-derived cells required.

Researchers wanted to understand the types of conversations that people have around serious illness, to identify the common features they have and determine if they follow common storylines.

New discovery for atomic-scale circuits brings closer the potential to eliminate a gigatonne of carbon emissions while increasing data capacities for ultra-efficient computers.